256 research outputs found

    Design Principles for Ligand-Sensing, Conformation-Switching Ribozymes

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    Nucleic acid sensor elements are proving increasingly useful in biotechnology and biomedical applications. A number of ligand-sensing, conformational-switching ribozymes (also known as allosteric ribozymes or aptazymes) have been generated by some combination of directed evolution or rational design. Such sensor elements typically fuse a molecular recognition domain (aptamer) with a catalytic signal generator (ribozyme). Although the rational design of aptazymes has begun to be explored, the relationships between the thermodynamics of aptazyme conformational changes and aptazyme performance in vitro and in vivo have not been examined in a quantitative framework. We have therefore developed a quantitative and predictive model for aptazymes as biosensors in vitro and as riboswitches in vivo. In the process, we have identified key relationships (or dimensionless parameters) that dictate aptazyme performance, and in consequence, established equations for precisely engineering aptazyme function. In particular, our analysis quantifies the intrinsic trade-off between ligand sensitivity and the dynamic range of activity. We were also able to determine how in vivo parameters, such as mRNA degradation rates, impact the design and function of aptazymes when used as riboswitches. Using this theoretical framework we were able to achieve quantitative agreement between our models and published data. In consequence, we are able to suggest experimental guidelines for quantitatively predicting the performance of aptazyme-based riboswitches. By identifying factors that limit the performance of previously published systems we were able to generate immediately testable hypotheses for their improvement. The robust theoretical framework and identified optimization parameters should now enable the precision design of aptazymes for biotechnological and clinical applications

    MIPs and Aptamers for Recognition of Proteins in Biomimetic Sensing

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    Biomimetic binders and catalysts have been generated in order to substitute the biological pendants in separation techniques and bioanalysis. The two major approaches use either “evolution in the test tube” of nucleotides for the preparation of aptamers or total chemical synthesis for molecularly imprinted polymers (MIPs). The reproducible production of aptamers is a clear advantage, whilst the preparation of MIPs typically leads to a population of polymers with different binding sites. The realization of binding sites in the total bulk of the MIPs results in a higher binding capacity, however, on the expense of the accessibility and exchange rate. Furthermore, the readout of the bound analyte is easier for aptamers since the integration of signal generating labels is well established. On the other hand, the overall negative charge of the nucleotides makes aptamers prone to non-specific adsorption of positively charged constituents of the sample and the “biological” degradation of non-modified aptamers and ionic strength-dependent changes of conformation may be challenging in some application

    Environmental Biosensors: A Microbiological View

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    In this mini-review, the potential of using microorganisms to design biosensors for detecting environmental pollutants is analyzed and discussed. A distinction is made between a classical biosensor (CB) and a whole-cell biosensor (WCB), emphasizing their structural components and the possibility of using whole microorganisms as their bioreceptor elements. The advantages and disadvantages of using prokaryotic microorganisms as opposed to eukaryotic microorganisms are described. Likewise, the advantages of using protozoa ciliates) over other eukaryotic microorganisms are also shown. We analyze the current bibliography on biosensors built on microorganisms as bioreceptors of pollutant molecules, such as inorganic (metal (loid)s) or organic (xenobiotics). New trends, such as the prokaryotic riboswitches, microbial two-component systems where the pollutant can be simultaneously detected and bioremediated, along with advances in synthetic biology, are shown as promising tools in the design of environmental biosensors

    Biosensor-based engineering of biosynthetic pathways

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    Biosynthetic pathways provide an enzymatic route from inexpensive renewable resources to valuable metabolic products such as pharmaceuticals and plastics. Designing these pathways is challenging due to the complexities of biology. Advances in the design and construction of genetic variants has enabled billions of cells, each possessing a slightly different metabolic design, to be rapidly generated. However, our ability to measure the quality of these designs lags by several orders of magnitude. Recent research has enabled cells to report their own success in chemical production through the use of genetically encoded biosensors. A new engineering discipline is emerging around the creation and application of biosensors. Biosensors, implemented in selections and screens to identify productive cells, are paving the way for a new era of biotechnological progress

    Towards Automated Design of Riboswitches

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    Experimental screening and selection pipelines for the discovery of novel riboswitches are expensive, time-consuming, and inefficient. Using computational methods to reduce the number of candidates for the screen could drastically decrease these costs. However, existing computational approaches do not fully satisfy all requirements for the design of such initial screening libraries. In this work, we present a new method, libLEARNA, capable of providing RNA focus libraries of diverse variable-length qualified candidates. Our novel structure-based design approach considers global properties as well as desired sequence and structure features. We demonstrate the benefits of our method by designing theophylline riboswitch libraries, following a previously published protocol, and yielding 30% more unique high-quality candidates.Comment: 9 pages, Accepted at the 2023 ICML Workshop on Computational Biolog
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